ΒιΆΉΣ°ΤΊ

Data and Analysis

Data and Analysis

This microcredential will provide a foundation for data and analysis. This is #3 of the K-12 Computer Science credential.

MICROCREDENTIAL ID: ETEC-KCS-0013
CREDENTIAL: K-12 Computer Science
CREDITS: 1.0 CEU (10 hours)
AUTHOR: Dr. Emily Baumgartner

 

Licensure Disclosure: EHHS Credentials and Microcredentials do not lead to an Ohio Department of Education (ODE) recognized licensure and/or endorsement preparation program. 

Registration

 

How to Earn This Microcredential

Participants will need to submit a set of evidence demonstrating their understanding of data systems and analysis and how these topics will be implemented in the curriculum. Additionally, participants will also complete a short written reflection analysis.

Fees

Participants submitting this microcredential for review will be assessed an administrative fee of $50. Participants who successfully complete the microcredential will receive a certificate showing completion of 1.0 CEU.

 Why Get This Microcredential?

 

This microcredential is part of the K-12 Computer Science credential. This microcredential will help the educator understand how data is stored and collected, and how data is analyzed. This credential must be completed sequentially starting with Microcredential #1 in the K-12 Computer Science credential. First, the educator gains background on computer and networking systems and how data gets stored. Next, the educator will gain experience in algorithms, which is an essential component prior to programming. The next microcredential will explore basic programming, which can be translated to many different activities in the classroom. Finally, the impacts of computing are explored in the last microcredential.

Important Terms
  • Data - Data is information that has been translated into a form that is efficient for movement or processing
  • Input βˆ’ In this step, the input data is prepared in some convenient form for processing. The form will depend on the processing machine. For example, when electronic computers are used, the input data can be recorded on any one of the several types of input medium, such as magnetic disks, tapes, and so on.
  • Processing βˆ’ In this step, the input data is changed to produce data in a more useful form. For example, pay-checks can be calculated from the time cards, or a summary of sales for the month can be calculated from the sales orders.
  • Output βˆ’ At this stage, the result of the proceeding processing step is collected. The particular form of the output data depends on the use of the data. For example, output data may be pay-checks for employees.
    • Retrieved from

  Benefits of this Microcredential

 

When a person uses a computer to write a document, their data is being stored somewhere. However, data does not always have to be saving a file. It can consist of maps, bar graphs, plots, or even databases. This microcredential will give participants a better understanding of how that data is stored and how it can be accessed and analyzed. Additionally, this topic is a good lead into algorithms and programming, which are the next microcredentials in this credential.

Standards

Ohio Learning Standards: Computer Science
  • DA.DCS - Data Collection and Storage
  • DA.VC -Visualization and Communication
    • Note: standards for Computer Science are categorized by grade level
CSTA Standards
  • CSTA Standards:
    • Specific standards are listed by grade level here:
      • Id. Use and Analyze Data
      • 3a. Pursue targeted professional development
      • 4a. Analyze CS curricula
      • 4b. Develop standards-aligned learning experiences

 Evidence Review

 

Candidates interested in earning this microcredential must submit three pieces of evidence: one piece related to learning, one related to implementing, and one related to reflecting.

When you are ready for your evidence review, submit your pieces of evidence for feedback from a qualified instructor. 

Learning

Required Resources

  • Read this page on computer memory:
  • Read this page on inputs and outputs:
  • View this video on β€œFinding files on your computer”  (3:10)
  • View this video on β€œCreating a simple bar chart in Excel” (1:22)

Additional Resources

  • File Tree basics
  • PBS Interactive Lesson on Data Analysis
  • Data analysis in Excel

Required Evidence

  • Create an Excel (or Sheets) bar graph with at least 10 bars. This information can show trending populations, students in sports, or any other topic. Insert the screenshot, as a separate page, into the document required below.
  • Submit a 1-2 page explaining how computers and software can store and analyze data.
    • Formatting – One to two pages maximum; double-spaced, no smaller than 11pt font.
    • Use references to support your claims. References do not count towards the 1-2 page minimum/maximum. Any format for references is allowed but APA is preferred.

Evidence Review Criteria

  • Criterion 1: Educator understands how data gets stored in a computer and within software.
  • Criterion 2: Educator can utilize software to store and analyze data.
Implementing

Required Resources

  • Read through this sample lesson plan (starting on p.192)

Additional Resources

  • Instructional strategies for CS:
  • INFOhio Curriculum ideas:
  • Code.org
  • Computer Science lesson plans:
  • Computer science unit plans:

Required Evidence

  • Submit a sample lesson plan implementing the Data and Analysis standards for your grade level.
  • Be sure to include the appropriate standards into your lesson:
    • Ohio (or your state’s) CS standards for your grade level :
    • CSTA standards for your grade level:
      • Sort by β€œComputing Systems”
  • Implement that lesson plan into the classroom.
  • Evidence of successful completion must include two components:
    • The lesson plan in Word or PDF format. There are no length or format requirements. However, it must have state or content standards included.
    • Include in the lesson plan the actual date(s) of implementation, including the age and grade of the audience.

Evidence Review Criteria

  • Evidence of preparation and planning
    • Criterion 1: Evidence demonstrates instructor applies applicable lesson to corresponding standard.
    • Criterion 2: Evidence demonstrates appropriate assessment for corresponding standard.
  • Evidence of Implementing
    • Criterion 1: Evidence demonstrates student understanding of corresponding standards.
Reflecting

Resources

  • If you are new to writing reflections, or this is your first microcredential, then please visit at least one of the additional resources.

Additional Resources

  • EduBirdie -
  • Trent University –

Required Evidence

  • Submit a document that considers these two questions:
    • What improvements could be made to the lesson plan previously implemented in this section?
    • What other aspects of data collection and analysis could be explored in other subject areas in the curricula?
  • Formatting – One to two pages maximum; double-spaced, no smaller than 11pt font.
  • No references are required.

Evidence Review Criteria

  • Criterion 1: The reflective analysis indicates the educator continually learns and increases their knowledge base.
  • Criterion 2: The reflective analysis identifies other appropriate areas for integration of CS curricula.
Β© 2024 ΒιΆΉΣ°ΤΊ All rights reserved.